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12th annual workshop on Research Design for Causal Inference at Northwestern Law School in Chicago, IL.
Main Workshop: Monday – Friday, August 7-11, 2023
Advanced Workshop: Monday – Thursday (midday, August 14-17, 2023
Optional Machine Learning Primer: Sunday afternoon, Aug. 13, 2023
What’s special about these workshops are the speakers. The session will be taught by world-class causal inference researchers, who are experts in the topics they will discuss. See below for details. In person-registration is limited to 125 participants for each workshop.
There will also be a Zoom option, but please come in person if you can. The online experience is not the same.
For information and to register:
https://www.law.northwestern.edu/research-faculty/events/conferences/causalinference/
Main Workshop Overview: Will cover the design of true randomized experiments and contrast them to natural or quasi experiments and to pure observational studies, where part of the sample is treated, the remainder is a control group, but the researcher controls neither which units are treated vs. control, nor administration of the treatment. We will assess the causal inferences one can draw from specific “causal” research designs, threats to valid causal inference, and research designs that can mitigate those threats.
Most empirical methods courses survey a variety of methods. We will begin instead with the goal of causal inference, and how to design a research plan to come closer to that goal, using messy, real-world datasets with limited sample sizes. The methods are often adapted to a particular study.
Advanced Workshop Overview: In-depth discussion of selected topics that are beyond what we can cover in the main workshop. The principal topics for 2023 are application of machine learning methods to causal inference; when and how to cluster standard errors, quantile and nonlinear difference-in-differences, doubly robust estimation of causal effects; difference-in-differences methods for staggered treatments (applied to different units at different times); and empirical Bayes approaches to estimating individual effects.
Target audience for main workshop: Quantitative empirical researchers (faculty and graduate students) in social science, including law, political science, economics, many business-school areas (finance, accounting, management, marketing, etc.), medicine, sociology, education, psychology, etc. –anywhere that causal inference is important.
We will assume knowledge, at the level of an upper-level undergraduate econometrics or similar course, of multivariate regression, including OLS, logit, and probit; basic probability and statistics including confidence intervals, t-statistics, and standard errors; and some understanding of instrumental variables.
Main Workshop: tuition is $900 ($600 for post-docs and graduate students; $500 if you are Northwestern-affiliated). .
Advanced Workshop: tuition is $650 ($450 for post-docs and graduate students; $300 if you are Northwestern affiliated).
Discount for attending both workshops: There is a $250 discount for non-Northwestern persons attending both workshops, for combined cost of $1,300 ($800 for post-docs and graduate students ($150 additional discount for Northwestern affiliates).
Zoom option: We are charging the same amount for in-person and virtual attendance.
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